1. Field of the Invention
The present invention is generally directed to the field of adaptive metrology sampling techniques, and, more particularly, to various methods and systems for adaptive metrology sampling plans that may be employed to monitor various manufacturing processes.
2. Description of the Related Art
In virtually all manufacturing environments, metrology data is acquired to ensure that various manufacturing processes are operating as expected and desired. In an ideal control situation, all metrology would be taken for all of the workpieces or material processed. However, in reality, such an exhaustive metrology sampling plan is not practical. Acquisition of metrology data does not add any value to the workpieces or material processed. Moreover, acquisition of metrology data is time-consuming and the acquisition process requires the use of expensive metrology tools and scarce metrology technicians or engineers. As such, there is a business-based desire to limit the amount of sampling done to a minimum level that is capable of providing useful information to monitor and control the various manufacturing processes.
In the context of semiconductor manufacturing operations, metrology sampling is generally performed as a set of fixed, independent rules as to which lots of wafers are to be sampled. For example, most previous sampling systems involve sampling based upon a fixed percentage, e.g., 20%, of the workpieces (or lots) processed through a tool or process operation, or based upon a preset pattern, e.g., every other lot (X-X-X), or measure the first workpiece and do not measure the next three (X - - - X - - - ). Additionally, ad hoc sampling decisions are sometimes also made at the discretion of the engineering department to increase the level of sampling at a particular tool or set of tools. Such multiple, uncoordinated sampling inputs may lead to over-sampling of a production line.
To reduce the risk of over-sampling, a common approach is to reduce the sampling rules to apply to only key process tools at a low rate. By taking this approach, the additional sampling from ad hoc decisions or other sources does not over-burden the capacity of the metrology tools and personnel. However, such a sampling approach introduces a risk that a problem with a non-key process tool could remain undetected due to the lack of a specific sampling rule for the non-key process tool.
By way of example only, in the context of a semiconductor manufacturing facility, it may be desirable to set up a metrology sampling plan to investigate potential etching defects. The process tools that may have an impact on causing such defects may be a collection of four etch tools and five solvent sinks (where photoresist mask material is stripped after the etch process is performed. A typical sampling rule may state that 30% of the lots processed through each of the four etch tools be subjected to metrology testing. However, the actual metrology testing is not performed until after the identified lots are processed through both an etch tool and one of the five solvent sinks. In adopting this approach, it is assumed that, due to randomness, the solvent sink tools will also be adequately sampled. However, in practice, such metrology may not provide adequate sampling of the non-key process tools, i.e., the solvent sinks. That is, due to random choice, the lots that are processed in the etch tools may not be equally distributed as they are processed downstream in the solvent sinks. As a result, some of the solvent sink tools may be over-sampled, while other solvent sink tools may be under-sampled.
Such a metrology sampling plan wherein it is assumed that all of the desired tools are being adequately samples is unacceptable for many manufacturing processes. Relying on such assumptions may lead to situations where a particular process tool that is not producing acceptable results may go undetected for a period of time. As a result, manufacturing costs increase and manufacturing efficiencies and yield may decrease. In general, what is desired is a metrology sampling methodology that minimizes the number of workpieces, e.g., lots, wafers, sampled while still adequately sampling the process tools and operations desired to be sampled.
The present invention is directed to various methods and systems that may solve, or at least reduce, some or all of the aforementioned problems.